Estimation of Actual Evapotranspiration Based on the Latest Modified Version of the Surface Energy Balance Algorithm Using Lysimeter Data

Document Type : Original Article

Authors

1 Department of Water Engineering, Faculty of Agricultural and Natural Resources, Imam Khomeini International University, Qazvin, Iran

2 Associated professor water Eng. Dept., Agricultural and natural resources Faculty, Imam Khomeini International University, Qazvin, Iran

Abstract

Evapotranspiration is one of the important components in planning and managing water and irrigation resources. Conventional methods of estimating evapotranspiration use point measurements, but in remote sensing techniques, such as the surface energy balance algorithm, the amount of instantaneous evapotranspiration flux during satellite transit as the remainder of the equation the energy balance is calculated for each pixel. In this study, two common mono-source evapotranspiration models estimated from SEBAL and PYSEBAL were compared with the results of a drainage lysimeter planted with alfalfa in the Qazvin plain. Satellite data were based on data from three sensors, MODIS, LANDSAT-5-TM and LANDSAT-7-ETM, from 2000 to 2003. The results of this study showed that the PYSEBAL model in all three sensors with RMSE (0.45, 0.46, and 2.02 mm/day) respectively had better performance than the SEBAL model. Also, the studies performed from the three sensors showed that the MODIS sensor with standard error value (0.15 mm / day) and correlation coefficient (0.98) compared to the two ETM and TM sensors with correlation coefficient values (0.97 and 0.53), standard error (0.17 and 2.26 mm/day) as well as higher spatial resolution have been able to produce better results.

Keywords


ابراهیمی پاک، ن. ع. 1379. تعیین تبخیر –تعرق پتانسیل گیاه مرجع (چمن) به روش لایسیمتر و مقایسه با روش­های تجربی در قزوین. وزارت جهاد کشاورزی، سازمان تحقیقات، آموزش و ترویج کشاورزی، مرکز تحقیقات کشاورزی و منابع طبیعی قزوین.
هدایتی دزفولی, ا. و کاکاوند، ر. 1391. پهنه‌بندی اقلیمی‌استان قزوین. نیوار. 36 (77–76): 59–66.
Allen, R G, Tasumi, M., Trezza, R., Waters, R. and Bastiaanssen, W. 2002. Surface Energy Balance Algorithm for Land (SEBAL)–Advanced training and Users Manual. Kimberly: Idaho Implementation.
Allen, Richard G., Tasumi, M. and Trezza, R. 2007. Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC)—Model. Journal of Irrigation and Drainage Engineering. 133(4): 380–394.
Almhab, A. A. and Busu, I. 2008. Estimation of Evapotranspiration with Modified SEBAL model using landsat-TM and NOAA-AVHRR images in arid mountains area. 2008 Second Asia International Conference on Modelling & Simulation (AMS). 350–355.
Bala, A., Rawat, K. S., Misra, A. K. and Srivastava, A. 2016. Assessment and validation of evapotranspiration using SEBAL algorithm and Lysimeter data of IARI agricultural farm, India. Geocarto International. 31(7): 739–764.
Bastiaanssen, Wilhelmus Gerardus Maria. 1995. Regionalization of surface flux densities and moisture indicators in composite terrain: A remote sensing approach under clear skies in Mediterranean climates. Wageningen University and Research.
Bastiaanssen, Wim G M, Menenti, M., Feddes, R. A. and Holtslag, A. A. M. 1998. A remote sensing surface energy balance algorithm for land (SEBAL). 1. Formulation. Journal of Hydrology. )212:(198–212.
Caiserman, A. and Faour, G. 2021. Spatial variability of evapotranspiration and pressure on groundwater resources: remote sensing monitoring by crop type in the Bekaa plain, Lebanon. Journal of Applied Remote Sensing. 15(1): 14517.
Carlson, T. N., Capehart, W. J. and Gillies, R. R. 1995. A new look at the simplified method for remote sensing of daily evapotranspiration. Remote Sensing of Environment. 54(2): 161–167.
Chang, X., Wang, S., Gao, Z., Luo, Y. and Chen, H. 2019. Forecast of daily reference evapotranspiration using a modified daily Thornthwaite equation and temperature forecasts. Irrigation and Drainage. 68(2): 297–317.
dos Santos, C. A. C., Mariano, D. A., Francisco das Chagas, A., Dantas, F. R. da C., de Oliveira, G., Silva, M. T., da Silva, L. L., da Silva, B. B., Bezerra, B. G., & Safa, B. 2020. Spatio-temporal patterns of energy exchange and evapotranspiration during an intense drought for drylands in Brazil. International Journal of Applied Earth Observation and Geoinformation. (85): 101982.
Elnmer, A., Khadr, M., Kanae, S. and Tawfik, A. 2019. Mapping daily and seasonally evapotranspiration using remote sensing techniques over the Nile delta. Agricultural Water Management. (213): 682–692.
Glenn, E.P., Neale, C.M.U., Hunsaker, D.J. and Nagler, P.L., 2011. Vegetation index-based crop coefficients to estimate evapotranspiration by remote sensing in agricultural and natural ecosystems. Hydrol. Process. )25:( 4050–4062.
Guo, Y., Zhao, X., Zhao, F., Jiao, Z., Zhou, X. and Yu, G. 2020. Tailoring surface wetting states for ultrafast solar-driven water evaporation. Energy & Environmental Science. 13(7): 2087–2095.
Hessels, T., van Opstal, J., Trambauer, P., Bastiaanssen, W., Faouzi, M., Mohamed, Y. and ErRaji, A. 2017. pySEBAL Version 3.3. 7.
Hunsaker, D.J., Pinter, P.J., Barnes, E.M. and Kimball, B.A., 2003. Estimating cotton evapotranspiration crop coefficients with a multispectral vegetation index. Irrigation Science. )22:( 95–104.
Jaafar, H. H. and Ahmad, F. A. 2020. Time series trends of Landsat-based ET using automated calibration in METRIC and SEBAL: The Bekaa Valley, Lebanon. Remote Sensing of Environment. (238): 111034.
Kamble, B., Irmak, A., Hubbard, K. and Gowda, P., 2013. Irrigation Scheduling Using Remote Sensing Data Assimilation Approach. 258–268
Nyolei, D., Nsaali, M., Minaya, V., van Griensven, A., Mbilinyi, B., Diels, J., Hessels, T. and Kahimba, F. 2019. High resolution mapping of agricultural water productivity using SEBAL in a cultivated African catchment, Tanzania. Physics and Chemistry of the Earth, Parts A/B/C. (112): 36–49.
Sawadogo, A., Gundogdu, K. S., Traoré, F., Kouadio, L. and Hessels, T. 2020.estimating i-season actual evapotranspiration over a large-scale irrigation scheme in resource-limited condition.Comptes Rendus de l’Académie Bulgare Des Sciences. 73(10).
Sawadogo, A., Hessels, T. İ. M., Gündoğdu, K. S., Demir, A. O., Mustafa, Ü. and Zwart, S. J. 2020.  comparative analysis of the PYSEBAL model and lysimeter for estimating actual evapotranspiration of soybean crop in Adana, Turkey. International Journal of Engineering and Geosciences. 5(2): 60–65.
Sun, Z., Wei, B., Su, W., Shen, W., Wang, C., You, D. and Liu, Z. 2011. Evapotranspiration estimation based on the SEBAL model in the Nansi Lake Wetland of China. Mathematical and Computer Modelling. 54(3–4): 1086–1092.
Zhang, K., Kimball, J. S. and Running, S. W. 2016. A review of remote sensing based actual evapotranspiration estimation. Wiley Interdisciplinary Reviews: Water. 3(6): 834–853.